dcor.ttest {energy} | R Documentation |
Distance correlation t-test of multivariate independence.
dcor.ttest(x, y, distance=FALSE) dcor.t(x, y, distance=FALSE)
x |
data or distances of first sample |
y |
data or distances of second sample |
distance |
logical: TRUE if x and y are distances |
dcor.ttest
performs a nonparametric t-test of
multivariate independence in high dimension (dimension is close to
or larger than sample size). The distribution of
the test statistic is approximately Student t with n(n-3)/2-1
degrees of freedom and for n ≥q 10 the statistic is approximately
distributed as standard normal.
The sample sizes (number of rows) of the two samples must
agree, and samples must not contain missing values. Arguments
x
, y
can optionally be dist
objects
or distance matrices (in this case set distance=TRUE
).
The t statistic is a transformation of a bias corrected version of distance correlation (see SR 2013 for details).
Large values (upper tail) of the t statistic are significant.
dcor.t
returns the t statistic, and
dcor.ttest
returns a list with class htest
containing
method |
description of test |
statistic |
observed value of the test statistic |
parameter |
degrees of freedom |
estimate |
(bias corrected) dCor(x,y) |
p.value |
p-value of the t-test |
data.name |
description of data |
Maria L. Rizzo mrizzo @ bgsu.edu and Gabor J. Szekely
Szekely, G.J. and Rizzo, M.L. (2013). The distance correlation t-test of independence in high dimension. Journal of Multivariate Analysis, Volume 117, pp. 193-213.
http://dx.doi.org/10.1016/j.jmva.2013.02.012
Szekely, G.J., Rizzo, M.L., and Bakirov, N.K. (2007),
Measuring and Testing Dependence by Correlation of Distances,
Annals of Statistics, Vol. 35 No. 6, pp. 2769-2794.
http://dx.doi.org/10.1214/009053607000000505
Szekely, G.J. and Rizzo, M.L. (2009),
Brownian Distance Covariance,
Annals of Applied Statistics,
Vol. 3, No. 4, 1236-1265.
http://dx.doi.org/10.1214/09-AOAS312
x <- matrix(rnorm(100), 10, 10) y <- matrix(runif(100), 10, 10) dx <- dist(x) dy <- dist(y) dcor.t(x, y) dcor.ttest(x, y)